Mark Paul

Exploring the roles of noise in the eukaryotic cell cycle

The DNA replication–division cycle of eukaryotic cells is controlled by a complex network of regulatory proteins, called cyclin-dependent kinases, and their activators and inhibitors. Although comprehensive and accurate deterministic models of the control system are available for yeast cells, reliable stochastic simulations have not been carried out because the full reaction network has yet to be expressed in terms of elementary reaction steps. As a first step in this direction, we present a simplified version of the control system that is suitable for exact stochastic simulation of intrinsic noise caused by molecular fluctuations and extrinsic noise because of unequal division. The model is consistent with many characteristic features of noisy cell cycle progression in yeast populations, including the observation that mRNAs are present in very low abundance (≈1 mRNA molecule per cell for each expressed gene). For the control system to operate reliably at such low mRNA levels, some specific mRNAs in our model must have very short half-lives (<1 min). If these mRNA molecules are longer-lived (perhaps 2 min), then the intrinsic noise in our simulations is too large, and there must be some additional noise suppression mechanisms at work in cells.

Stochastic dynamics of nanoscale mechanical oscillators immersed in a viscous fluid

The stochastic response of nanoscale oscillators of arbitrary geometry immersed in a viscous fluid is studied. Using the fluctuation-dissipation theorem, it is shown that deterministic calculations of the governing fluid and solid equations can be used in a straightforward manner to directly calculate the stochastic response that would be measured in experiment. We use this approach to investigate the fluid coupled motion of single and multiple cantilevers with experimentally motivated geometries.

A model of yeast cell-cycle regulation based on multisite phosphorylation

In order for the cells genome to be passed intact from one generation to the next, the events of the cell cycle (DNA replication, mitosis, cell division) must be executed in the correct order, despite the considerable molecular noise inherent in any protein‐based regulatory system residing in the small confines of a eukaryotic cell. To assess the effects of molecular fluctuations on cell‐cycle progression in budding yeast cells, we have constructed a new model of the regulation of Cln‐ and Clb‐dependent kinases, based on multisite phosphorylation of their target proteins and on positive and negative feedback loops involving the kinases themselves. To account for the significant role of noise in the transcription and translation steps of gene expression, the model includes mRNAs as well as proteins. The model equations are simulated deterministically and stochastically to reveal the bistable switching behavior on which proper cell‐cycle progression depends and to show that this behavior is robust to the level of molecular noise expected in yeast‐sized cells (∼50 fL volume). The model gives a quantitatively accurate account of the variability observed in the G1‐S transition in budding yeast, which is governed by an underlying sizer+timer control system.

Extensive chaos in the Lorenz-96 model.

We explore the high-dimensional chaotic dynamics of the Lorenz-96 model by computing the variation of the fractal dimension with system parameters. The Lorenz-96 model is a continuous in time and discrete in space model first proposed by Lorenz to study fundamental issues regarding the forecasting of spatially extended chaotic systems such as the atmosphere. First, we explore the spatiotemporal chaos limit by increasing the system size while holding the magnitude of the external forcing constant. Second, we explore the strong driving limit by increasing the external forcing while holding the system size fixed. As the system size is increased for small values of the forcing we find dynamical states that alternate between periodic and chaotic dynamics. The windows of chaos are extensive, on average, with relative deviations from extensivity on the order of 20%. For intermediate values of the forcing we find chaotic dynamics for all system sizes past a critical value. The fractal dimension exhibits a maximum deviation from extensivity on the order of 5% for small changes in system size and the deviation from extensivity decreases nonmonotonically with increasing system size. The length scale describing the deviations from extensivity is consistent with the natural chaotic length scale in support of the suggestion that deviations from extensivity are due to the addition of chaotic degrees of freedom as the system size is increased. We find that each wavelength of the deviation from extensive chaos contains on the order of two chaotic degrees of freedom. As the forcing is increased, at constant system size, the dimension density grows monotonically and saturates at a value less than unity. We use this to quantify the decreasing size of chaotic degrees of freedom with increased forcing which we compare with spatial features of the patterns.

The stochastic dynamics of micron and nanoscale elastic cantilevers in fluid: fluctuations from dissipation

The stochastic dynamics of micron and nanoscale cantilevers immersed in a viscous fluid are quantified. Analytical results are presented for long slender cantilevers driven by Brownian noise. The spectral density of the noise force is not assumed to be white and the frequency dependence of the noise force is determined from the fluctuation-dissipation theorem. The analytical results are shown to be useful for the micron scale cantilevers that are commonly used in atomic force microscopy. A general thermodynamic approach is developed that is valid for cantilevers of arbitrary geometry as well as for arrays of multiple cantilevers whose stochastic motion is coupled through the fluid. It is shown that the fluctuation-dissipation theorem permits the calculation of stochastic quantities via straightforward deterministic methods. The thermodynamic approach is used with deterministic finite element numerical simulations to quantify the auto-correlation and noise spectrum of cantilever fluctuations for a single micron scale cantilever and the cross-correlations and noise spectra of fluctuations for an array of two experimentally motivated nanoscale cantilevers as a function of cantilever separation. The results are used to quantify the noise reduction possible using correlated measurements with two closely spaced nanoscale cantilevers.

The nonlinear dynamics of tapping mode atomic force microscopy with capillary force interactions

We study the nonlinear dynamics of a tapping mode atomic force microscope with tip-surface interactions that include attractive, repulsive, and capillary force contributions using numerical techniques tailored for hybrid or discontinuous dynamical systems that include forward-time simulation with event handling and numerical pseudo-arclength continuation. We find four branches of periodic solutions that are separated by windows of complex and irregular dynamics. The branches of periodic solutions end where the cantilever comes into grazing contact with event surfaces in state space, corresponding to the onset of capillary interactions and the onset of repulsive forces associated with contact. These windows of irregular dynamics are found to coexist with the periodic branches of solutions as well as exist beyond the termination of the periodic solution. Finally, we show that these details can be overlooked unless one is careful to sample the dynamics appropriately.

Dynamical eigenfunction decomposition of turbulent pipe flow

The results of an analysis of turbulent pipe flow based on a Karhunen–Loeve decomposition are presented. The turbulent flow is generated by a direct numerical simulation of the Navier–Stokes equations using a spectral element algorithm at a Reynolds number Reτ = 150. This simulation yields a set of basis functions that captures 90% of the energy after 2763 modes. The eigenfunctions are categorized into two classes and six subclasses based on their wavenumber and coherent vorticity structure. Of the total energy, 81% is in the propagating class, characterized by constant phase speeds; the remaining energy is found in the non-propagating subclasses, the shear and roll modes. The four subclasses of the propagating modes are the wall, lift, asymmetric and ring modes. The wall modes display coherent vorticity structures near the wall, the lift modes display coherent vorticity structures that lift away from the wall, the asymmetric modes break the symmetry about the axis, and the ring modes display rings of coh...

Pattern formation and dynamics in Rayleigh-Benard convection : numerical simulations of experimentally realistic geometries.

Abstract Rayleigh–Benard convection is studied and quantitative comparisons are made, where possible, between theory and experiment by performing numerical simulations of the Boussinesq equations for a variety of experimentally realistic situations. Rectangular and cylindrical geometries of varying aspect ratios for experimental boundary conditions, including fins and spatial ramps in plate separation, are examined with particular attention paid to the role of the mean flow. A small cylindrical convection layer bounded laterally either by a rigid wall, fin, or a ramp is investigated and our results suggest that the mean flow plays an important role in the observed wavenumber. Analytical results are developed quantifying the mean flow sources, generated by amplitude gradients, and its effect on the pattern wavenumber for a large-aspect-ratio cylinder with a ramped boundary. Numerical results are found to agree well with these analytical predictions. We gain further insight into the role of mean flow in pattern dynamics by employing a novel method of quenching the mean flow numerically. Simulations of a spiral defect chaos state where the mean flow is suddenly quenched is found to remove the time dependence, increase the wavenumber and make the pattern more angular in nature.

BioNEMS: Nanomechanical Systems for Single-Molecule Biophysics

Techniques from nanoscience now enable the creation of ultrasmall electronic devices. Among these, nanoelectromechanical systems (NEMS) in particular offer unprecedented opportunities for sensitive chemical, biological, and physical measurements [1]. For vacuum-based applications NEMS provide extremely high force and mass sensitivity, ultimately below the attonewton and single-Dalton level respectively. In fluidic media, even though the high quality factors attainable in vacuum become precipitously damped due to fluid coupling, extremely small device size and high compliance still yield force sensitivity at the piconewton level - i.e., smaller than that, on average, required to break individual hydrogen bonds that are the fundamental structural elements underlying molecular recognition processes. A profound and unique new feature of nanoscale fluid-based mechanical sensors is that they offer the advantage of unprecedented signal bandwidth (»1 MHz), even at piconewton force levels. Their combined sensitivity and temporal resolution is destined to enable real-time observations of stochastic single-molecular biochemical processes down to the sub-microsecond regime [2].

Event-driven feedback tracking and control of tapping-mode atomic force microscopy

This paper presents an event-driven, discrete-in-time feedback strategy for tracking and stabilizing naturally occurring periodic oscillations in the probe-tip dynamics of atomic force microscope (AFM) cantilevers in tapping-mode operation. Specifically, robust dynamic tracking and stabilization is achieved by the imposition of discrete changes in the vertical offset between the cantilever support and the sample surface based on an estimated linearization of the system dynamics about a dynamically generated reference trajectory. Here, use is made not only of the oscillation amplitude, as is typical in commercial control implementations for AFMs, but also of the instantaneous phase information. It is shown that stabilization and desirable performance during surface scanning is possible, even in the presence of uncertainty and limited state access. In particular, the methodology enables robust tracking and use of low-contact-velocity periodic system responses that are unstable in the absence of control.